学习交通事故类型的分类

2012 Fourth International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2012-09-19 DOI:10.1109/INCOS.2012.75

Tibebe Beshah, D. Ejigu, P. Krömer, V. Snás̃el, J. Platoš, A. Abraham

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引用次数: 16

摘要

提出了一种基于进化模糊分类器的道路交通事故数据分析方法。利用遗传规划进化出的模糊分类器，对实际道路交通事故数据集进行标注学习。对符号分类器进行了检验，以选择重要特征及其之间的关系。选定的功能可以为交通管理部门提供反馈，从而可以利用这些知识来改善道路安全和减轻交通事故的严重程度。

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Learning the Classification of Traffic Accident Types

This paper presents an application of evolutionary fuzzy classifier design to a road accident data analysis. A fuzzy classifier evolved by the genetic programming was used to learn the labeling of data in a real world road accident data set. The symbolic classifier was inspected in order to select important features and the relations among them. Selected features provide a feedback for traffic management authorities that can exploit the knowledge to improve road safety and mitigate the severity of traffic accidents.

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2012 Fourth International Conference on Intelligent Networking and Collaborative Systems

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